Mohd Saufee Muhammad

Application of Particle Swarm Optimization in Histogram Equalization for image enhancement

The basic and most common technique for contrast adjustment in the image is using Histogram Equalization (HE). It is based on equalizing the histogram of the image and subsequently enhancing its contrast, and results in overall contrast improvement. This paper introduces a combination of normal HE technique and Particle Swarm Optimization (PSO) algorithm for enhancing distorted image naturally. The process is as follows. The image is separated into red, green and blue (RGB) channels and PSO algorithm is applied into each channel in order to get its best fitness value. The fitness value that is obtained then will be applied into HEs normalization, after that the processed color image will be merged back to RGB image. Experimental results have shown the effectiveness in improving the contrast of the original images without introducing disturbing artifacts caused by normal HE.

An improved binary particle swarm optimization algorithm for DNA encoding enhancement

The accuracy of DNA computing highly depends on the DNA strands used in solving complex computations. As such, many approaches are proposed to design DNA oligonucleotides that are stable and unique. In this paper, an improved binary particle swarm optimization (IBPSO) algorithm is proposed and implemented. Four objective functions which are H-measure, similarity, hairpin and continuity are employed to define the uniqueness of designed sequences. The DNA words are constrained within a predefined range of GC-content and melting temperature. The performances and the ability of the algorithm to enhance the characteristics of generated DNA code words are analyzed. The results obtained show that this algorithm executes better sequences and did perform better compared to other optimization techniques. Moreover, it converges faster than the previously suggested binary particle swarm optimization algorithm.

DNA computing for complex scheduling problem

Interest in DNA computing has increased overwhelmly since Adleman successfully demonstrated its capability to solve Hamiltonian Path Problem (HPP). Many research results of similar combinatorial problems which are mainly in the realm of computer science and mathematics have been presented. In this paper, implementation ideas and methods to solve an engineering related combinatorial problem using this DNA computing approach is presented. The objective is to find an optimal path for a complex elevator scheduling problem of an 8-storey building with 3 elevators. Each of the elevator traveled path is represented by DNA sequence of specific length that represent elevators traveling time in a proportional way based on certain initial conditions such as present and destination floors, and hall calls for an elevator from a floor. The proposed ideas and methods show promising results that DNA computing approach can be well-suited for solving such real-world application in the near future.

DNA implementation of k-shortest paths computation

In this paper, a demonstration of DNA computing for k-shortest paths of a weighted graph is realized by biochemical experiments in such a way that every path is encoded by oligonucleotides and the length of the path is directly proportional to the length of oligonucleotides. For initial pool generation, parallel overlap assembly is employed for efficient generation of all candidate answers. During the computation, after the initial pool of solution is subjected to amplification, which is polymerase chain reaction, k-shortest paths could be separated by gel electrophoresis and the selection can be made at last

Solving Elevator Scheduling Problem Using DNA Computing Approach

DNA computing approach has gained wide interest in recent years since Adleman shows that the technique can be used to solve the Hamiltonian Path Problem (HPP). Since then there has been many research results showing how DNA computing is used to solve a variety of similar combinatorial problems which is mainly in the realm of computer science. However, the application of DNA computing in solving engineering related problems has not been well established. In this paper we demonstrate how DNA computing can be used to solve a two-elevator scheduling problem for a six-storey building. The research involves finding a suitable technique to represent the DNA sequences in finding the optimal route for each elevator based on initial conditions such as the present position of the elevator, the destination of passengers in the elevators and hall calls from a floor. The approach shows that the DNA computing approach can be well-suited for solving such real-world application in the near future.

Sound navigation aid system for the vision impaired

Visually impaired or blind people are someone who lost their ability to see. They usually depend on guide cane or guide dog to assist them navigates their environment. However, guide cane requires the blind to scan the surrounding manually with their hand while guide dog is expensive and has a short life span. There are many researches on creating better navigation aid for blind people. Instead of using vibration or alarm to notify the distance of the obstacles, this research proposed the application of sound notification for the blind. This system is developed using MATLAB r2010a with the integrated webcam of the laptop and a laser pointer. The laser pointer acts as a reference point so that objects distance can be calculated from the captured image by the webcam. This system manages to calculate distance for any color of object under any level of brightness condition during day and night time. It also possesses human head movement ability to turn left and right, up and down. This system managed to detect the obstacles up to a distance of 432 centimeters, which is sufficient to prevent the blind from bumping into the obstacles. The calculated distance is then converted to sound in order to notify the blind how far the object is away from them.

Direct-Proportional Length-Based DNA Computing Implementation for Elevator Scheduling Problem

Implementation and experimental procedures to solve an elevator scheduling problem using direct-proportional length-based DNA computing approach are presented in this paper. All possible travel path combinations of the elevators are encoded by oligonucleotides of length directly proportional to the elevators traveling time based on certain initial conditions such as elevators present and destination floors, and hall calls from a floor. Parallel overlap assembly is employed for initial pool generation and polymerase chain reaction for amplification. Gel electrophoresis is then performed to separate all the generated travel paths by its oligonucleotides lengths. The gel electrophoresis image is then captured to visualize the required optimal path. Experimental result shows that DNA computing approach can be well-suited for solving such real-world problem of this type of nature.

Satellite Image Segmentation with the Application of PSO Algorithm

Satellite imaging consists of capturing images of the Earth through a series of artificial satellites. These images contain an abundance of information that can be used in several applications such as fishing, agriculture, regional planning, biodiversity conservation and many others. Digital image processing can help overcome the limitations of human vision by extracting key information from these images at a much higher rate through the speed of automation. This paper aims to achieve that by exploiting the potential of the Particle Swarm Optimization (PSO) algorithm in image segmentation. Various satellite images were segmented using PSO algorithm before a trace of the objects that have been isolated in the image was run to evaluate the accuracy of segmentation. Three objective measurements which are Peak Signal to Noise Ratio (PSNR), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE), were made on the outputs of the segmentation using PSO algorithm and the traditional segmentation technique which is Otsu’s method for comparison. The proposed method which applies the PSO algorithm proved to be superior in producing images of higher quality and accuracy as compared to the traditional segmentation technique.

Ensembles of DNA letters for the design of unique DNA library using a modified version of multi-criteria VEDEPSO optimizer

The DNA code words designing is a multi-criteria combinatorial optimization task. The designed words should be as unique as possible, thermodynamically stable, non-self hybridized, non-cross hybridized with others and have good chemical properties. In this paper, the DNA words designing approach implied concurrent minimizations of four objective functions, H-measure, similarity, hairpin and continuity. The designations is subjected to a predefine range of melting temperature and GC-content. A novel multi-population optimizer, M-VEDEPSO, is employed to design sets of DNA strands. The algorithm runs for 10 times and as a result, each population has lower average fitness values compared to the fitness values obtained using the conventional VEDEPSO algorithm. The results obtained from the algorithm are indicated by 12 randomly selected non-dominated particles/individuals. These solutions are obtained via Pareto dominance concepts.

Development of Portable Finger Clubbing Meter

Finger clubbing, also known as drumstick finger, is the medical symptom that is indicated by the development of the sponginess or swelling in the nail beds of nails and toes. The higher grade of clubbing on the patients can be easily identified with the presence of drumstick finger. The existing available measurement device to identify the early stage of clubbing required much time which is impractical for a busy clinic practice. This paper explains the determination of the finger clubbing by using the Digital Index (DI) measurement, which was deployed by implementing and developing the Portable Finger Clubbing Meter hardware and the Microsoft Visual Basic (VB) Graphical User Interface (GUI). Finger circumference values of nail-fold (NF) and distal interphalangeal joint (DIP) of twenty participants were measured using the developed hardware. Data analysis was then performed using the GUI for DI computation, and the presence of finger clubbing could be determined.